{"id":"W2967460745","doi":"10.3390/info10080257","title":"Visual Saliency Prediction Based on Deep Learning","year":2019,"lang":"en","type":"article","venue":"Information","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Memorial University of Newfoundland","funders":"Ministry of Higher Education and Scientific Research","keywords":"Artificial intelligence; Computer science; Deep learning; Convolutional neural network; Categorical variable; Pattern recognition (psychology); Segmentation; Transfer of learning; Saliency map; Kadir–Brady saliency detector; Pixel; Encoder; Computer vision; Image (mathematics); Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002372244,0.0000755196,0.00005917414,0.0002186444,0.0001129683,0.0001614701,0.0001517278,0.0000553068,0.00007333589],"category_scores_gemma":[0.00003578272,0.00007097435,0.00004276136,0.0003179542,0.000006390428,0.002465912,0.0000260564,0.0001283443,0.002296414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005796948,"about_ca_system_score_gemma":0.00001838712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005073799,"about_ca_topic_score_gemma":5.243424e-7,"domain_scores_codex":[0.9991573,0.00004292701,0.0002235427,0.000107112,0.0003382983,0.0001307979],"domain_scores_gemma":[0.9996014,0.00002228827,0.0001101357,0.0001502742,0.00007638575,0.00003946322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000631553,0.0001560792,0.01666636,0.0000834622,0.00001018793,7.648061e-7,0.002446361,0.1584174,0.001521491,0.02945369,0.0004015228,0.7907795],"study_design_scores_gemma":[0.0003491601,0.0004261248,0.02985736,0.00001354411,0.000001184487,0.000002183002,0.00006229703,0.9618436,0.0006792706,0.00009562437,0.006588782,0.00008090679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1520213,0.000001560588,0.8247975,0.0001323536,0.0009408183,0.0001819268,5.293413e-7,0.0004256011,0.02149845],"genre_scores_gemma":[0.9985754,0.000001325053,0.0007247736,0.0005005438,0.00002622868,0.00001056611,0.00002677706,0.000002677134,0.0001316825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8465542,"threshold_uncertainty_score":0.9984804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004704822597397344,"score_gpt":0.2276714225538344,"score_spread":0.222966599956437,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}